ai-agent-reliability

ai-agent-reliability is an LLM evaluation & observability skill for AI agents, published by mohitagw15856 in the pm-claude-skills repository on GitHub. Skillspace rates ai-agent-reliability D (68/100) and it passed the safety scan; the rating is based on static analysis only.

Make an AI agent or automation reliable enough to trust — the tests, checks, and guardrails that catch its failures before they reach anything real. Use when asked how do I test my AI agent, make my automation reliable, my agent works sometimes, or how do I trust an AI workflow in production. Produces a map of where the agent can fail (bad input, hallucination, wrong tool call, edge cases, silent errors), the checks that catch each (validation, evals on real cases, human-in-the-loop gates, monitoring), a right-sized reliability plan scaled to the stakes, and a rollout that earns trust incrementally — so an agent that works in a demo becomes one that works in reality. For builders putting AI agents into real workflows.

Grade

D

Quality

68 / 100

Safety

Passed

GitHub stars

1,361

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